Percutaneous coronary intervention with drug-eluting stents versus coronary bypass surgery for coronary artery disease: A Bayesian perspective
Bibliographic record
Abstract
OBJECTIVES: Coronary revascularization is frequently performed for coronary artery disease (CAD). This study aims to assess the totality of randomized evidence comparing percutaneous coronary intervention with drug-eluting stents (DES-PCI) with coronary artery bypass grafting (CABG) for CAD. METHODS: A systematic search was applied to 3 electronic databases, including randomized trials comparing DES-PCI with CABG for CAD with 5-year follow-up. A Bayesian hierarchical meta-analytic model was applied. The primary outcome was all-cause mortality at 5 years; secondary outcomes were stroke, myocardial infarction, and repeat revascularization. End points were reported in median relative risks (RRs) and absolute risk differences, with 95% credible intervals (CrIs). Kaplan-Meier curves were used to reconstruct individual patient data. RESULTS: Six studies comprising 8269 patients (DES-PCI, n = 4134; CABG, n = 4135) were included. All-cause mortality at 5 years was increased with DES-PCI (median RR, 1.23; 95% CrI, 1.01-1.45), with a median absolute risk difference of +2.3% (95% CrI, 0.1%-4.5%). For stroke, myocardial infarction, and repeat revascularization, the median RRs were 0.79 (95% CrI, 0.54-1.25), 1.84 (95% CrI, 1.23-2.75), and 1.80 (95% CrI, 1.51-2.16) for DES-PCI, respectively. In a sample of 1000 patients undergoing DES-PCI instead of CABG for CAD, a median of 23 additional deaths, 46 myocardial infarctions, and 85 repeat revascularizations occurred at 5 years, whereas 10 strokes were prevented. CONCLUSIONS: The current data suggest a clinically relevant benefit of CABG over DES-PCI at 5 years in terms of mortality, myocardial infarction, and repeat revascularization, despite an increased risk of stroke. These findings may guide the heart-team and the shared decision-making process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".